A Real Time 1080P 30FPS Gaussian Mixture Modeling Design for Background Subtraction And Object Extraction

Abstract

The Gaussian Mixture Modeling (GMM) algorithm with connected component labeling as object extraction provide robust background subtraction but suffer from complexity, and large buffer or high bandwidth due to the frame level operations. For real time application needs, this paper proposed a block based GMM design for background subtraction with message passing between blocks to avoid performance drop. The corresponding parallel hardware design can reach real time 1080P@30fps and cost 164.82K gate-counts at 125MHz with 90nm process.